mc2-scripts-and-benchmarks.git - Benchmarks and execution scripts for testing spatial isolation and SMT interference in MC^2

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author	Joshua Bakita <jbakita@cs.unc.edu>	2020-10-17 21:36:21 -0400
committer	Joshua Bakita <jbakita@cs.unc.edu>	2020-10-17 21:36:21 -0400
commit	e5db76ee18640ce27df8756e573ef8b497af4750 (patch)
tree	8442b5f064f93c02906f4ef48cdb478cf627b4d2 /dis/inputs/Pointer/in2
parent	ecf6547fdce39b3ec0f333c9b391b0f1c25deba5 (diff)

All the TACLeBench runner scripts as used for the (rejected) RTSS'20 submission

Everything without isolation: run_tacle_rtss20.sh For isolation you have to run the hodgepodge of scripts as before.

Diffstat (limited to 'dis/inputs/Pointer/in2')

0 files changed, 0 insertions, 0 deletions

n>1,2,4,0), converters={0: lambda n: name_id_map[n.decode("utf_8")]}) names = np.unique(data[:,3]) for name in names: yield (data[data[:,3] == name][:,:-1], id_name_map[int(name)]) # Subsamples one benchmark at a specific WSS def plot_exec_vs_cache_data(data, ax, wss, **kwargs): wsss = np.unique(data[:,0]) # Get exec time for this working set size with all ways allocated divisor = data[np.logical_and(data[:,0] == wss, data[:,1] == 16.0)][0,2] # Normalize relative to that exec time one_wss_data = data[data[:,0] == wss] / [1,1,divisor] # Plot max exec time vs cache allocation return ax.plot(np.flip(one_wss_data[:,1],0), np.flip(one_wss_data[:,2],0), **kwargs) # Wrapper function for backwards compatibility def plot_exec_vs_cache(filename, ax, wss, line='-'): data = np.loadtxt(filename, usecols=(1,2,4)) plot_exec_vs_cache_data(data, ax, wss, linestyle=line, label=filename.split("-")[-4]) # Styles and colors which match those used in the paper name_to_label = {"matrix":"-", "transitive":"-.", "neighborhood":"--", "pointer":":", "update":"-", "field":"-."} name_to_color = {"matrix":"C0", "transitive":"C1", "neighborhood":"C2", "pointer":"C3", "update":"C4", "field":"C5"} plt.rcParams["font.family"] = "serif" plt.rcParams['figure.figsize'] = [6, 4] legend_labels = [] wss = 4 * 2**20 fig, ax = plt.subplots() ax.set_xlabel("Cache Half Ways Allocated") ax.set_ylabel("Worst-Case Execution Time Multiplier") for (data, name) in multibench_file(sys.argv[1]): line, = plot_exec_vs_cache_data(data, ax, wss, linestyle=name_to_label[name], label=name, color=name_to_color[name]) # Save the max plotted value and legend info legend_labels.append((max(line.get_ydata()), line, name)) # Sort the legend by the max plotted value legend_labels.sort(key=lambda k: k[0], reverse=True) ax.legend([x[1] for x in legend_labels], [x[2] for x in legend_labels]) # Plot from most to least ways allocated ax.set_xlim(ax.get_xlim()[::-1]) fig.savefig("exec_vs_cache_4mb_ae.pdf") print("Plot saved as exec_vs_cache_4mb_ae.pdf")


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